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Online course materials for MATH10282Introduction to Statistics
Unit code: | MATH10282 |
Credit Rating: | 10 |
Unit level: | Level 1 |
Teaching period(s): | Semester 2 |
Offered by | School of Mathematics |
Available as a free choice unit?: | N |
Requisites
Prerequisite- MATH10141 - Probability 1 (Compulsory)
Aims
The aims of this course unit are to help students
develop a knowledge of basic statistical concepts and methodology which build on the ideas in probability studied in MATH10141;
develop practical statistical skills.
Overview
The course gives a general introduction to statistics and is a prerequisite for all future statistics courses.
Learning outcomes
On successful completion of this course unit students will be able to
understand introductory statistical ideas and methodology;
use the statistical computing software R to analyse data.
Future topics requiring this course unit
The statistics content is required for MATH20802, Statistical Methods and MATH20812, Practical Statistics 1. The background in R is also very useful for MATH20812, Practical Statistics I.
Assessment methods
- Other - 20%
- Written exam - 80%
Assessment Further Information
Two coursework assignments (20%) plus a two hour end of semester examination (80%).
Syllabus
Populations and samples, random sampling. [1]
Representing sample data the histogram, boxplot, numerical summary measures. [2]
Probability models for data. [2]
Sampling distributions of sample statistics - the sample mean and its distribution under Normality, using the Central Limit Theorem, the sample proportion, the sample variance, the chi-squared distribution. [2]
Point estimation the bias and variance of an estimator, choosing between competing estimators. [2]
The likelihood function and maximum likelihood estimators for discrete variables. [2]
Confidence intervals. Single sample procedures for a Normal mean and variance, the population proportion. Two sample procedures for the difference between two Normal means and the difference between two population proportions. [3]
Hypothesis testing introductory ideas and concepts. [2]
Tests based on a single sample the Normal mean (variance known and unknown), the Normal variance, a non-Normal mean parameter, the Binomial probability parameter. Relationship between CIs and hypothesis testing. [3]
Calculation of the probability of rejecting the null for a given value of the population parameter. [1]
Tests based on two independent samples for differences between two Normal means, two non-Normal means, two population proportions. [2
Recommended reading
G M Clarke and D Cooke, A Basic Course in Statistics (Fourth Edition) Oxford University Press, 1998;
Robert V Hogg, Introduction to Mathematical Statistics (Sixth Edition) Prentice Hall, 2005;
Sheldon M Ross, Introduction to Probability and Statistics for Engineers and Scientists (Third edition) Elsevier Science, 2004;
Michael J Crawley, Statistics: An Introduction Using R. John Wiley & Sons Ltd, 2007
Feedback methods
Feedback supervision will provide an opportunity for students' work to be discussed and provide feedback on their understanding. Coursework or in-class tests (where applicable) also provide an opportunity for students to receive feedback. Students can also get feedback on their understanding directly from the lecturer, for example during the lecturer's office hour.
Study hours
- Lectures - 22 hours
- Tutorials - 11 hours
- Independent study hours - 67 hours
Teaching staff
Timothy Waite - Unit coordinator